1st Edition
Handbook of Item Response Theory Volume 1: Models
Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume One: Models presents all major item response models. This first volume in a three-volume set covers many model developments that have occurred in item response theory (IRT) during the last 20 years. It describes models for different response formats or response processes, the need of deeper parameterization due to a multilevel or hierarchical structure of the response data, and other extensions and insights.
In Volume One, all chapters have a common format with each chapter focusing on one family of models or modeling approach. An introductory section in every chapter includes some history of the model and a motivation of its relevance. Subsequent sections present the model more formally, treat the estimation of its parameters, show how to evaluate its fit to empirical data, illustrate the use of the model through an empirical example, and discuss further applications and remaining research issues.
Introduction
Wim J. van der Linden
Dichotomous Models
Unidimensional Logistic Models
Wim J. van der Linden
Rasch Model
Matthias von Davier
Nominal and Ordinal Models
Nominal Categories Models
David Thissen and Li Cai
Rasch Rating Scale Model
David Andrich
Graded Response Models
Fumiko Samejima
Partial Credit Model
Geoff N. Masters
Generalized Partial Credit Model
Eiji Muraki and Mari Muraki
Sequential Models for Ordered Responses
Gerhard Tutz
Models for Continuous Responses
Gideon J. Mellenbergh
Multidimensional and Multicomponent Models
Normal-Ogive Multidimensional Models
Hariharan Swaminathan and H. Jane Rogers
Logistic Multidimensional Models
Mark D. Reckase
Linear Logistic Models
Rianne Janssen
Multicomponent Models
Susan E. Embretson
Models for Response Times
Poisson and Gamma Models for Reading Speed and Error
Margo G. H. Jansen
Lognormal Response-Time Model
Wim J. van der Linden
Diffusion-Based Response-Time Models
Francis Tuerlinckx, Dylan Molenaar, and Han L. J. van der Maas
Nonparametric Models
Mokken Models
Klaas Sijtsma and Ivo W. Molenaar
Bayesian Nonparametric Response Models
George Karabatsos
Functional Approaches to Modeling Response Data
James Ramsay
Models for Nonmonotone Items
Hyperbolic Cosine Model for Unfolding Responses
David Andrich
Generalized Graded Unfolding Model
James S. Roberts
Hierarchical Response Models
Logistic Mixture-Distribution Response Models
Matthias von Davier and Jürgen Rost
Multilevel Response Models with Covariates and Multiple Groups
Jean-Paul Fox and Cees A. W. Glas
Two-Tier Item Factor Analysis Modeling
Li Cai
Item-Family Models
Cees A. W. Glas, Wim J. van der Linden, and Hanneke Geerlings
Hierarchical Rater Models
Jodi M. Casabianca, Brian W. Junker, and Richard J. Patz
Randomized Response Models for Sensitive Measurements
Jean-Paul Fox
Joint Hierarchical Modeling of Responses and Response Times
Wim J. van der Linden and Jean-Paul Fox
Generalized Modeling Approaches
Generalized Linear Latent and Mixed Modeling
Sophia Rabe-Hesketh and Anders Skrondal
Multidimensional, Multilevel, and Multi-Timepoint Item Response Modeling
Bengt Muthén and Tihomir Asparouhov
Mixed-Coefficients Multinomial Logit Models
Raymond. J. Adams, Mark R. Wilson, and Margaret L. Wu
Explanatory Response Models
Paul De Boeck and Mark R. Wilson
Biography
Wim J. van der Linden is a distinguished scientist and director of research innovation at Pacific Metrics Corporation. He is also a professor emeritus of measurement and data analysis at the University of Twente. He is a past president of the Psychometric Society and National Council on Measurement in Education (NCME) and a recipient of career achievement awards from NCME, Association of Test Publishers (ATP), and American Educational Research Association (AERA). His research interests include test theory, computerized adaptive testing, optimal test assembly, parameter linking, test equating, and response-time modeling as well as decision theory and its application to problems of educational decision making. Dr. van der Linden earned a PhD in psychometrics from the University of Amsterdam.
"Handbook I is likely to be useful for undergraduate or graduate students who have an interest in pursuing quantitative research in educational and psychological testing, especially with datasets that contain multiple discrete outcomes. Master- and doctoral-level students seeking dissertation topics and doing literature reviews will find Handbook I a valuable resource."
~Edward H. Ip, Wake Forest School of Medicine, Journal of the American Statistical Association